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Related Concept Videos

Epistasis Analysis01:09

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
Quantitative Aspects of Drug-Receptor Interaction01:30

Quantitative Aspects of Drug-Receptor Interaction

The receptor occupancy theory connects a drug's response to the number of occupied receptors. With higher drug concentrations, more receptors are occupied, leading to increased responses. The formation of drug-receptor complexes involves association and dissociation rates, which reach equilibrium when the forward and backward reactions are equal. The equilibrium association constant (Ka) and its inverse, the equilibrium dissociation constant (Kd), indicate drug affinity. Higher Ka and lower Kd...
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.In the early 20th century,...
Incomplete Dominance01:43

Incomplete Dominance

Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
Epistasis01:39

Epistasis

In addition to multiple alleles at the same locus influencing traits, numerous genes or alleles at different locations may interact and influence phenotypes in a phenomenon called epistasis. For example, rabbit fur can be black or brown depending on whether the animal is homozygous dominant or heterozygous at a TYRP1 locus. However, if the rabbit is also homozygous recessive at a locus on the tyrosinase gene (TYR), it will have an unshaded coat that appears white, regardless of its TYRP1...
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...

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Related Experiment Video

Updated: Jun 17, 2026

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

Towards accurate imputation of quantitative genetic interactions.

Igor Ulitsky1, Nevan J Krogan, Ron Shamir

  • 1Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. ulitsky@wi.mit.edu

Genome Biology
|December 17, 2009
PubMed
Summary

Researchers developed a new method to predict missing genetic interactions in yeast. This approach combines genetic data with genomic information to uncover nearly 190,000 new interactions.

Related Experiment Videos

Last Updated: Jun 17, 2026

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

Area of Science:

  • Genetics and Genomics
  • Systems Biology
  • Computational Biology

Background:

  • High-throughput screening enables large-scale measurement of genetic interactions in Saccharomyces cerevisiae.
  • Current assays frequently miss a significant proportion (up to 40%) of gene pair interactions, limiting comprehensive analysis.

Purpose of the Study:

  • To develop and present a novel computational method for quantitatively imputing missing genetic interactions.
  • To leverage diverse genomic data alongside existing genetic interaction data for improved prediction accuracy.

Main Methods:

  • Integration of quantitative genetic interaction data with multiple types of genomic datasets.
  • Development of a novel imputation algorithm to predict missing gene pair interactions.

Main Results:

  • Successful imputation of missing genetic interactions, significantly expanding the known interaction network.
  • Discovery and presentation of data for approximately 190,000 novel genetic interactions.

Conclusions:

  • The developed imputation method effectively addresses the challenge of missing data in high-throughput genetic interaction screens.
  • This work provides a substantially expanded map of genetic interactions in Saccharomyces cerevisiae, facilitating deeper systems-level understanding.